RL
Reinforcement learning from verifiable outcomes
Topic
What experts have said about Reinforcement learning from verifiable outcomes
3 statements · 1 positive · 2 negative
RLVR scales by repeatedly testing models on increasingly difficult verifiable problems.
“with RLVR you literally give the model well, you let the model solve more and more complex, difficult problems.”
Open the episode · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGIListen at 2:08:45
Training on verifiable outcomes is doomed if human-like learners are near.
“If we're actually close to a human-like learner, then this whole approach of training on verifiable outcomes is doomed.”
Open the episode · An audio version of my blog post, Thoughts on AI progress (Dec 2025)Listen at 0:07
No well-fitting public scaling trend is known for reinforcement learning from verifiable reward.
“for which we have no well-fit publicly known trend.”
Open the episode · An audio version of my blog post, Thoughts on AI progress (Dec 2025)Listen at 8:51
Statements are attributed to the speaker as said on the episode and reflect their view at the time, not PodLume's. They are not advice.